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Abstract Background Lumbar puncture is challenging for patients with scoliosis. Previous ultrasound-assisted techniques for lumbar puncture used the angle of the probe as the needle trajectory; however, reproducing the angle is difficult and increases the number of needle manipulations. In response, we developed a technique that eliminated both the craniocaudal and lateromedial angulation of the needle trajectory to overall improve this technique. We assessed the feasibility and safety of this method in patients with scoliosis and identify factors related to difficult lumbar puncture. Methods Patients with spinal muscular atrophy and scoliosis who were referred to the anesthesia department for intrathecal nusinersen administrations were included. With a novel approach that utilized patient position and geometry, lumbar puncture was performed under ultrasound guidance. Success rates, performance times and adverse events were recorded. Clinical-demographic and spinal radiographic data pertaining to difficult procedures were analyzed. Results Success was achieved in all 260 (100%) lumbar punctures for 44 patients, with first pass and first attempt success rates of 70% (183/260) and 87% (226/260), respectively. Adverse events were infrequent and benign. Higher BMI, greater skin dural sac depth and smaller interlaminar size might be associated with greater difficulty in lumbar puncture. Conclusions The novel ultrasound-assisted horizontal and perpendicular interlaminar needle trajectory approach is an effective and safe method for lumbar puncture in patients with spinal deformities. This method can be reliably performed at the bedside and avoids other more typical and complex imaging such as computed tomography guided procedure.

Abstract Background Acute myocardial infarction (AMI) and diabetic nephropathy (DN) are common clinical co-morbidities, but they are challenging to manage and have poor prognoses. There is no research on the bioinformatics mechanisms of comorbidity, and this study aims to investigate such mechanisms. Methods We downloaded the AMI data (GSE66360) and DN datasets (GSE30528 and GSE30529) from the Gene Expression Omnibus (GEO) platform. The GSE66360 dataset was divided into two parts: the training set and the validation set, and GSE30529 was used as the training set and GSE30528 as the validation set. After identifying the common differentially expressed genes (DEGs) in AMI and DN in the training set, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses and protein–protein interaction (PPI) network construction were performed. A sub-network graph was constructed by MCODE, and 15 hub genes were screened by the Cytohubba plugin. The screened hub genes were validated, and the 15 screened hub genes were subjected to GO, KEGG, Gene MANIA analysis, and transcription factor (TF) prediction. Finally, we performed TF differential analysis, enrichment analysis, and TF and gene regulatory network construction. Results A total of 46 genes (43 up-regulated and 3 down-regulated) were identified for subsequent analysis. GO functional analysis emphasized the presence of genes mainly in the vesicle membrane and secretory granule membrane involved in antigen processing and presentation, lipopeptide binding, NAD + nucleosidase activity, and Toll-like receptor binding. The KEGG pathways analyzed were mainly in the phagosome, neutrophil extracellular trap formation, natural killer cell-mediated cytotoxicity, apoptosis, Fc gamma R-mediated phagocytosis, and Toll-like receptor signaling pathways. Eight co-expressed hub genes were identified and validated, namely TLR2, FCER1G, CD163, CTSS, CLEC4A, IGSF6, NCF2, and MS4A6A. Three transcription factors were identified and validated in AMI, namely NFKB1, HIF1A, and SPI1. Conclusions Our study reveals the common pathogenesis of AMI and DN. These common pathways and hub genes may provide new ideas for further mechanistic studies.

Abstract Background Chronic shoulder and neck pain is one of the most common chronic occupational disorders, with an average incidence rate of 48.5%, severely affecting patients’ quality of life and ability to work. According to epidemiological research, the prevalence of chronic neck, shoulder, and low back pain in adults over the age of 45 ranges from 40 to 80%. According to reports, medical staff have a higher incidence rate than other populations, and there is a positive correlation between the grade of the medical institution and the incidence rate, making medical staff a priority group for the prevention of chronic neck, shoulder, and low back pain. By the end of 2022, China has been fully opened to epidemic prevention and control, the total number of patients in domestic hospitals has increased significantly, and resulting in medical personnel shoulting great pressure, which seriously affects the physical and mental health of medical personnel. The aim of this study was to explore the risk factors of chronic neck, shoulder and lumbar back pain in medical staff. To provide guidelines for medical staff to improve cervical and lumbar subacute pain and reduce the emergence of spinal lesions. Methods From January to February 2023, 602 staff members of a third-grade hospital in Zunyi City were studied by Questionnaire star. Univariate and multivariate Logistic regression were used to analyze the independent risk factors of chronic neck, shoulder and lumbar back pain in medical staff, with stepwise regression utilized to choose the optimum model. The model was selected using Akaike’s information criterion (AIC) and the Hosmer-Lemeshow goodness-of-fit test. Results A total of 602 medical staff were polled, and the findings revealed that 588 cases of chronic neck, shoulder, and low back pain of varied severity had occurred in the previous 1 to 2 years, with a 97.7% incidence rate; logistic regression analysis revealed that anxiety level, frequency of bending over in the previous 1 to 2 years, whether related preventive measures were taken at work, gender, positive senior title, daily ambulation time, and whether the department they worked in organized independent influencing factors. Conclusion The incidence of chronic neck, shoulder, and lumbar back pain among medical staff is high; its influencing factors are different and have not been systematically identified. Hospitals should take effective measures tailored to local conditions to improve the physical and mental health of medical staff.

Abstract Background Heart failure (HF) is a disease that poses a serious threat to individual health, and DNA methylation is an important mechanism in epigenetics, and its role in the occurrence and development of the disease has attracted more and more attention. The aim of this study was to evaluate the link between iodothyronine deiodinase 3 promoter region fragment FA27 (DIO3-FA27) methylation levels, biochemical indices, and HF. Results The methylation levels of DIO3-FA27_CpG_11.12 and DIO3-FA27_CpG_23.24 significantly differed in HF patients with different degrees. Multivariate logistic regression analysis indicated that the relative HF risk in the third and fourth quartiles of activated partial thromboplastin time and fibrin degradation products. The results of the restricted cubic spline model showed that the methylation levels of DIO3-FA 27_CpG_11.12 and DIO3-FA 27_CpG_23.24 were associated with coagulation indicators, liver function, renal function, and blood routine. Conclusions Based on the differential analysis of CpG methylation levels based on DIO3-FA27, it was found that biochemical indicators combined with DIO3-FA27 promoter DNA methylation levels could increase the risk of worsening the severity classification of HF patients, which provided a solid foundation and new insights for the study of epigenetic regulation mechanisms in patients with HF.

Abstract Background Acinetobacter baumannii (A. baumannii) is associated with both hospital-acquired infections (HAP) and community-acquired pneumonia (CAP). In this study, we present a novel CAP-associated A. baumannii (CAP-AB) strain causing severe pneumonia in an afore healthy male patient without underlying conditions. Subsequently, we investigated the pathogenicity and immunogenicity of this CAP-AB strain using a mice pneumonia model. Results A 58-year-old male patient with no underlying conditions experienced worsening symptoms of a productive cough, sputum, and fever that developed acutely, in just 24 h. The diagnosis was severe community-acquired pneumonia (CAP) and type-1 respiratory failure. An A. baumannii strain was isolated from his sputum and blood cultures. To gain a deeper understanding of the rapid progression of its pathology, we utilized the CAP-associated A. baumannii strain YC128, a previously obtained hospital-acquired pneumonia A. baumannii (HAP-AB) strain YC156, and a highly virulent A. baumannii control strain LAC-4 to construct a mouse pneumonia model, and subsequently compared the mortality rate of the three groups. Following inoculation with 107 CFU of A. baumannii, the mortality rate for the YC128, LAC-4, and YC156 groups was 60% (6/10), 30% (3/10), and 0%, respectively. The bacterial burden within the pulmonary, liver, and spleen tissues of mice in the YC128 group was significantly higher than that of the YC156 group, and slightly higher than that of the LAC-4 group. Pathological analysis of lung tissue using HE-staining revealed that the inflammatory pathological changes in mice from the YC128 group were significantly more severe than those in the YC156 group. Additionally, CT scan images displayed more pronounced inflammation in the lungs of mice from the YC128 group compared to the YC156 group. Local levels of cytokines/chemokines such as IL-1β, IL-6, TNF-α, and CXCL1 were assessed via RT-qPCR in lung tissues. In comparison with the YC156 strain, the highly virulent YC128 strain induced the expression of proinflammatory cytokines more rapidly and severely. Furthermore, we examined the in vitro anti-phagocytosis ability of YC128 and YC156 strains against mice peritoneal macrophages, revealing that the highly virulent YC128 isolate displayed greater resistance to macrophage uptake in contrast to YC156. Results from Whole Genome Sequencing (WGS) indicated that YC128 harbored a complete type VI secretion system (T6SS) gene cluster, while YC156 lacked the majority of genes within the T6SS gene cluster. The other virulence-related genes exhibited minimal differences between YC128 and YC156. Drawing from previous studies, we postulated that the T6SS is linked to the hypervirulence and robust anti-phagocytic ability of YC128. Conclusions This article reports on the isolation of a novel hypervirulent CAP-AB strain, YC128, from a severe CAP patient. The results demonstrate that this CAP-AB strain, YC128, is capable of inducing fatal pneumonia and extrapulmonary dissemination in a mouse pneumonia model. Moreover, this highly virulent CAP-AB strain exhibits significantly stronger anti-phagocytic abilities compared to the HAP-AB YC156 strain. Genome sequencing comparisons reveal that the heightened hypervirulence and enhanced anti-phagocytosis abilities observed in YC128 may be attributed to the presence of the T6SS.

The impact of rhizosphere aeration on the composition of xylem sap in cucumber grown in soil was studied to determine its effects on (i) water and nutrient uptake, (ii) xylem transport, and (iii) amino acid synthesis in the roots. Plants grown under three different aeration conditions were subjected to progressive gas stress throughout the whole growth period. The shoot and root growth, xylem nitrate (NO3-) concentration, potassium (K+) concentration, xylem sap flow rate, and amino acid concentrations were higher in the Z1 treatment plants than in the control (CK) plants, and the former also showed a lower CO2 (0.25-0.84%) and a higher O2 (18.22-20.02%). However, the Z3 treatment plants exhibited decreased xylem loading of amino acids, NO3- concentrations, and K+ concentrations and a lower flow rate of xylem sap, which restricted shoot and root growth due to poor aeration caused by a higher CO2 (0.75-3.68%) and a lower O2 (11.51-18.6%). Furthermore, the xylem pH in these plants was lower by approximately 0.17 units, and the conductivity was decreased by approximately 0.31 mS/cm. Based on the observed results, the CO2 and O2 in the soil can potentially regulate root and shoot growth and the xylem sap composition in cucumber. Therefore, rhizosphere aeration is important for the vigorous growth of plants.

Abstract Background Colorectal cancer (CRC) is a complex malignancy characterized by diverse molecular profiles, clinical outcomes, and limited precision in prognostic markers. Addressing these challenges, this study utilized multi-omics data to define consensus molecular subtypes in CRC and elucidate their association with clinical outcomes and underlying biological processes. Methods Consensus molecular subtypes were obtained by applying ten integrated multi-omics clustering algorithms to analyze TCGA-CRC multi-omics data, including mRNA, lncRNA, miRNA, DNA methylation CpG sites, and somatic mutation data. The association of subtypes with prognoses, enrichment functions, immune status, and genomic alterations were further analyzed. Next, we conducted univariate Cox and Lasso regression analyses to investigate the potential prognostic application of biomarkers associated with multi-omics subtypes derived from weighted gene co-expression network analysis (WGCNA). The function of one of the biomarkers MID2 was validated in CRC cell lines. Results Two CRC subtypes linked to distinct clinical outcomes were identified in TCGA-CRC cohort and validated with three external datasets. The CS1 subtype exhibited a poor prognosis and was characterized by higher tumor-related Hallmark pathway activity and lower metabolism pathway activity. In addition, the CS1 was predicted to have less immunotherapy responder and exhibited more genomic alteration compared to CS2. Then a prognostic model comprising five genes was established, with patients in the high-risk group showing substantial concordance with the CS1 subtype, and those in the low-risk group with the CS2 subtype. The gene MID2, included in the prognostic model, was found to be correlated with epithelial–mesenchymal transition (EMT) pathway and distinct DNA methylation patterns. Knockdown of MID2 in CRC cells resulted in reduced colony formation, migration, and invasion capacities. Conclusion The integrative multi-omics subtypes proposed potential biomarkers for CRC and provided valuable knowledge for precision oncology.

Abstract Chinese media companies are facing opportunities and challenges brought about by digital transformation. Media economics takes the evaluation of the business results of media companies as the main research topic. However, overcoming the internal differences in the industry and comprehensively predicting the digital transformation of Chinese media companies from multiple dimensions has become an important issue to be understood. Based on the “TOE-I” theoretical framework, this study innovatively uses machine learning methods to predict the digital transformation of Chinese media companies and to analyze specific modes of the main driving factors affecting the digital transformation, using data from China’s A-share-listed media companies from 2010 to 2020. The study found that environmental drivers can most effectively and accurately predict the digital transformation of Chinese media companies. Therefore, under sustained and stable economic and financial policies, guiding inter-industry competition and providing balanced digital infrastructure conditions are keys to bridging internal barriers in the media industry and promoting digital transformation. In the process of transformation from traditional content to digital production, media companies should focus on policy changes, economic benefits, the decision-making role of core managers, and the training and preservation of digital technology talent.

Abstract With advanced science and digital technology, digital transformation has become an important way to promote the sustainable development of enterprises. However, the existing research only focuses on the linear relationship between a single characteristic and digital transformation. In this study, we select the data of Chinese A-share listed companies from 2010 to 2020, innovatively use the machine learning method and explore the differences in the predictive effects of multi-dimensional features on the digital transformation of enterprises based on the Technology-Organization-Environment (TOE) theory, thus identifying the main drivers affecting digital transformation and the fitting models with stronger predictive effect. The study found that: first, by comparing machine learning and traditional linear regression models, it is found that the prediction ability of ensemble earning method is generally higher than that of tradition measurement method. For the sample data selected in this research, XGBoost and LightGBM have strong explanatory ability and high prediction accuracy. Second, compared with the technical driving force and environmental driving force, the organizational driving force has a greater impact. Third, among these characteristics, equity concentration and executives’ knowledge level in organizational dimension have the greatest impact on digital transformation. Therefore, enterprise managers should always pay attention to the decision-making role of equity concentration and executives’ knowledge level. This study further enriches the literature on digital transformation in enterprises, expands the application of machine learning in economics, and provides a theoretical basis for enterprises to enhance digital transformation.

Abstract Digital transformation has emerged as a powerful force in reshaping the business landscape and enabling organizations to enhance their capabilities. One critical aspect of this change is how it impacts an enterprise’s innovation ability. To explore this question, we select data regarding China’s A-share listed enterprises from 2007 to 2021 as the research sample. We employ crawler technology to gather keywords related to “digital transformation” from annual reports, portraying detailed journeys of enterprises’ digital transformation. Through descriptive statistics and multiple covariance tests, a linear relationship is established between digital transformation and innovation ability. Benchmark regression is conducted and a robustness test is utilized to determine the robustness of the benchmark regression. The mechanism, heterogeneity, and moderating effects of this study are also tested. The results reveal that digital transformation makes a significant positive contribution to the innovation capability of enterprises. Meanwhile, among different types of enterprises, the impact of digital transformation on enterprise innovation capability shows heterogeneity. In terms of the impact mechanism, digital transformation can enhance the innovation output of enterprises by reducing the agency cost and improving the risk-taking level of enterprises, so as to further improve the innovation capability of enterprises. The research results of this paper provide essential theoretical support for the digital transformation of enterprises and the government’s formulation of enterprises’ digitalization strategies. More profoundly, it provides significant reference for how to further promote the digital transformation of Chinese enterprises.

Abstract In an era where digital technology is reshaping business landscapes, understanding the factors that drive corporate digital transformation is essential. In this paper we explore these influencing factors, focusing on Chinese A-share listed companies from 2007 to 2021. Our approach involved a comprehensive analysis of multiple variables through regression techniques to determine their impact on digital transformation. The findings reveal the drive for reform in the digital transformation endeavours of enterprises. Notably, companies with higher gearing, overhead, and accounts receivable ratios exhibit a stronger inclination towards digital transformation. Conversely, enterprises in monopolistic industries and those at the inception stage of their life cycle show less propensity for such transformation. The findings of this research not only shed light on the strategic decisions behind digital transformation in response to financial and competitive challenges but also provide actionable insights for policymakers and business strategists. This study underscores the importance of contextualizing digital transformation efforts within the unique framework of industry characteristics and company development phases.

Abstract Developing strain sensors with both high sensitivity and high linearity has always been the goal of researchers. Compared to resistive strain sensors, capacitive strain sensors have incomparable linearity advantages, but have always been limited by low sensitivity. Here, we report a gradient stiffness sliding design strategy that addresses this problem, significantly improving sensitivity while maintaining high linearity. By controlling the distribution of the locally enhanced electric field and the heterogeneous deformation of the substrate, a strain sensor with excellent performance is successfully prepared, exhibiting a giant gauge factor (9.1 × 106) and linearity (R 2 = 0.9997) over the entire sensing range, together with almost no hysteresis and fast response time (17 ms). The gradient stiffness sliding design is a general strategy expected to be applied to other types of sensors to achieve ultra-high sensitivity and ultra-high linearity at the same time.

Abstract Natural killer (NK) cells are unique from other immune cells in that they can rapidly kill multiple neighboring cells without the need for antigenic pre-sensitization once the cells display surface markers associated with oncogenic transformation. Given the dynamic role of NK cells in tumor surveillance, NK cell-based immunotherapy is rapidly becoming a "new force" in tumor immunotherapy. However, challenges remain in the use of NK cell immunotherapy in the treatment of solid tumors. Many metabolic features of the tumor microenvironment (TME) of solid tumors, including oxygen and nutrient (e.g., glucose, amino acids) deprivation, accumulation of specific metabolites (e.g., lactate, adenosine), and limited availability of signaling molecules that allow for metabolic reorganization, multifactorial shaping of the immune-suppressing TME impairs tumor-infiltrating NK cell function. This becomes a key barrier limiting the success of NK cell immunotherapy in solid tumors. Restoration of endogenous NK cells in the TME or overt transfer of functionally improved NK cells holds great promise in cancer therapy. In this paper, we summarize the metabolic biology of NK cells, discuss the effects of TME on NK cell metabolism and effector functions, and review emerging strategies for targeting metabolism-improved NK cell immunotherapy in the TME to circumvent these barriers to achieve superior efficacy of NK cell immunotherapy.

Introduction: The epithelial immunomodulation and regeneration are intrinsic critical events against inflammatory bowel disease (IBD). MiR-7 is well documented as a promising regulator in the development of various diseases including inflammatory diseases. Objectives: This study aimed to assess the effect of miR-7 in intestinal epithelial cells (IECs) in IBD. Methods: MiR-7def mice were given dextran sulfate sodium (DSS) to induce enteritis model. The infiltration of inflammatory cells was measured by FCM and immunofluorescence assay. 5′deletion assay and EMSA assays were performed to study the regulatory mechanism of miR-7 expression in IECs. The inflammatory signals and the targets of miR-7 were analyzed by RNA-seq and FISH assay. IECs were isolated from miR-7def, miR-7oe and WT mice to identify the immunomodulation and regeneration capacity. IEC-specific miR-7 silencing expression vector was designed and administered by the tail vein into murine DSS-induced enteritis model to evaluate the pathological lesions of IBD. Results: We found miR-7 deficiency improved the pathological lesions of DSS-induced murine enteritis model, accompanied by elevated proliferation and enhanced transduction of NF-κB/AKT/ERK signals in colonic IECs, as well as decreased local infiltration of inflammatory cells. MiR-7 was dominantly upregulated in colonic IECs in colitis. Moreover, the transcription of pre-miR-7a-1, orchestrated by transcription factor C/EBPα, was a main resource of mature miR-7 in IECs. As for the mechanism, EGFR, a miR-7 target gene, was downregulated in colonic IECs in colitis model and Crohn's disease patients. Furthermore, miR-7 also controlled the proliferation and inflammatory-cytokine secretion of IECs in response to inflammatory-signals through EGFR/NF-κB/AKT/ERK pathway. Finally, IEC-specific miR-7 silencing promoted the proliferation and transduction of NF-κB pathway in IECs and alleviated the pathological damage of colitis. Conclusion: Our results present the unknown role of miR-7/EGFR axis in IEC immunomodulation and regeneration in IBD and might provide clues for the application of miRNA-based therapeutic strategies in colonic diseases.

Abstract Background Myocardial injury after noncardiac surgery (MINS) is one of the most common complications associated with postoperative adverse cardiovascular outcomes and mortality. However, MINS often fails to be timely diagnosed due to the absence of clinical symptoms and limited diagnostic methods. The metabolomic analysis might be an efficient way to discover new biomarkers of MINS. Characterizing the metabolomic features of MINS patients may provide new insight into the diagnosis of MINS. Methods In this study, serum samples from 20 matched patients with or without MINS (n = 10 per group) were subjected to untargeted metabolomics analysis to investigate comprehensive metabolic information. Differential metabolites were identified, and the enriched metabolic pathway was determined based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Results A comprehensive analysis revealed 124 distinct metabolites, predominantly encompassing lipids, amino acids and other compounds. The observed modifications in metabolic pathways in patients with or without MINS showed significant clustering in cholesterol metabolism, aldosterone synthesis and secretion, primary bile acid biosynthesis, as well as cysteine and methionine metabolism. Four specific metabolites (taurocholic acid, L-pyroglutamic acid, taurochenodeoxycholic acid, and pyridoxamine) exhibited promising potential as biomarkers for prognosticating MINS. Conclusions This study contributes valuable insights into the metabolomic features of MINS and the discovery of potential biomarkers which may help the early diagnosis of MINS. The identified metabolites and altered pathways offer valuable insights into the molecular underpinnings of MINS, paving the way for improved diagnostic approaches and potential intervention strategies.

Abstract Background The recently discovered PcAA14A and B from white-rot basidiomycete Pycnoporus coccineus enriched our understanding of the oxidative degradation of xylan in fungi, however, the unusual mode of action of AA14 LPMOs has sparked controversy. The substrate specificity and functionality of AA14 LPMOs still remain enigmatic and need further investigation. Results In this study, a novel AA14 LPMO was characterized from the ascomycete Talaromyces rugulosus. TrAA14A has a broad substrate specificity with strong oxidative activity on pure amorphous cellulose and xyloglucan. It could simultaneously oxidize cellulose, xylan and xyloglucan in natural hemi/cellulosic substrate such as fibrillated eucalyptus pulp, and released native and oxidized cello-oligosaccharides, xylo-oligosaccharides and xyloglucan oligosaccharides from this substrate, but its cellulolytic/hemicellulolytic activity became weaker as the contents of xylan increase in the alkaline-extracted hemi/cellulosic substrates. The dual cellulolytic/hemicellulolytic activity enables TrAA14A to possess a profound boosting effect on cellulose hydrolysis by cellulolytic enzymes. Structure modelling of TrAA14A revealed that it exhibits a relatively flat active-site surface similar to the active-site surfaces in AA9 LPMOs but quite distinct from PcAA14B, despite TrAA14A is strongly clustered together with AA14 LPMOs. Remarkable difference in electrostatic potentials of L2 and L3 surfaces was also observed among TrAA14A, PcAA14B and NcLPMO9F. We speculated that the unique feature in substrate-binding surface might contribute to the cellulolytic/hemicellulolytic activity of TrAA14A. Conclusions The extensive cellulolytic/hemicellulolytic activity on natural hemi/cellulosic substrate indicated that TrAA14A from ascomycete is distinctively different from previously characterized xylan-active AA9 or AA14 LPMOs. It may play as a bifunctional enzyme to decompose some specific network structures formed between cellulose and hemicellulose in the plant cell walls. Our findings shed new insights into the novel substrate specificities and biological functionalities of AA14 LPMOs, and will contribute to developing novel bifunctional LPMOs as the booster in commercial cellulase cocktails to efficiently break down the hemicellulose-cellulose matrix in lignocellulose.

Abstract To evaluate the association of uric acid (UA) with adverse outcomes and its potential mediator in patients with left ventricular diastolic dysfunction (LVDD) and pulmonary hypertension (PH). We retrospectively analyzed 234 patients with LVDD and PH. The baseline characteristics of patients with low UA (≤ 330 µmol/L) group were compared with high UA (> 330 µmol/L) group. Adverse outcomes included all-cause mortality, cardiac death and heart failure (HF) hospitalization. Their association with UA and the mediator were evaluated using Cox regression and mediation analysis. The mediation proportion was further quantified by the R mediation package. During a mean follow-up of 50 ± 18 months, there were 27 all-cause deaths, 18 cardiovascular deaths and 41 incidents of HF hospitalization. Multivariable Cox regression analysis showed UA was an independent risk factor of adverse outcomes in LVDD and PH patients, even after adjusting for age, sex, body mass index, medical histories, systolic blood pressure, fasting blood glucose, total cholesterol, triglyceride, eGFR, BNP and medications. The hazard ratios (HRs) for UA (per 10 µmol/L increase) were as below: for all-cause mortality, HR 1.143, 95% CI 1.069–1.221, P

For the project of pipe jacking in cohesionless soil, it is key to determine the vertical load on jacked pipe so as to predict the jacking force accurately. In this paper, a new parabolic soil arching model was proposed to calculate the vertical load on jacked pipe. This proposed analytical model was composed of parabolic soil arching zone, parabola-typed collapse zone and friction arch zone. Combined with existing literature, the key parameters (i.e., height of parabolic soil arching, horizontal pressure coefficient and width and height of friction arch) were determined. In addition, considering that the trajectory of major stress is parabola, the formula of horizontal pressure coefficient was deduced in the friction arch. The parabolic soil arching zone is assumed as a three-hinged arch with reasonable arch axis, and the formula of load transfer was derived considering the transition effect of parabolic soil arching. The results of experiment, theoretical models and numerical model were adopted to verify the proposed analytical model. Finally, the influence of the key parameters on the vertical load on jacked pipe were also discussed in detail. This work provides a meaningful reference for evaluating the vertical load on jacked pipe for design of pipe jacking.

BackgroundHypotension is a risk factor for postoperative complications, but evidence from randomized trials does not support that a higher blood pressure target always leads to optimized outcomes. The heterogeneity of underlying hemodynamics during hypotension may contribute to these contradictory results. Exploring the subtypes of hypotension can enable optimal management of intraoperative hypotension.MethodsThis is a prospective, observational pilot study. Patients who were ≥ 45 years old and scheduled to undergo moderate-to-high-risk noncardiac surgery were enrolled in this study. The primary objective of this pilot study was to investigate the frequency and distribution of perioperative hypotension and its subtypes (hypotension with or without cardiac output reduction). The exposure of hypotension and its subtypes in patients with and without myocardial or acute kidney injury were also explored.ResultsSixty patients were included in the analysis. 83% (50/60) of the patients experienced perioperative hypotension. The median duration of hypotension for each patient was 8.0 [interquartile range, 3.1–23.3] minutes. Reduced cardiac output was present during 77% of the hypotension duration. Patients suffering from postoperative myocardial or acute kidney injury displayed longer duration and more extensive exposure in all hypotension subtypes. However, the percentage of different hypotension subtypes did not differ in patients with or without postoperative myocardial or acute kidney injury.ConclusionPerioperative hypotension was frequently accompanied by cardiac output reduction in moderate-to-high-risk noncardiac surgical patients. However, due to the pilot nature of this study, the relationship between hypotension subtypes and postoperative myocardial or acute kidney injury still needs further exploration.Clinical trial registrationhttps://www.chictr.org.cn/showprojEN.html?proj=134260, CTR2200055929.

Background and objectivesAnastomotic leakage (AL) is one of the most serious complications after laparoscopic anus-preserving surgery for rectal cancer, which significantly prolongs the patient’s hospital stay, leads to dysfunction, and even increases the patient’s perioperative morbidity and mortality, and little is known about the effectiveness of anastomotic reinforcement sutures to prevent AL. Thus, this study was conducted to evaluate the efficacy of anastomotic reinforcement sutures as a means to prevent AL during laparoscopic surgery for rectal cancer.MethodsA comprehensive and systematic search was performed in the literature database by combining subject and free terms up to 10 October 2023. The overall literature included was integrated and analyzed using Stata 12.0 software and Review Manager version 5.4 software to assess the effect of anastomotic reinforcement sutures on the incidence of AL.ResultsA total of 2,452 patients from 14 studies were included, and an integrated analysis showed that the use of anastomotic reinforcement sutures significantly reduced the incidence of AL [odds ratio (OR) = 0.26; 95% confidence interval (CI), 0.18–0.37; P < 0.00001; I2 = 0%]. However, the findings confirmed whether or not the anastomosis reinforced with sutures did not affect the incidence of anastomotic stenosis (OR = 0.69; 95% CI, 0.37–1.32; P = 0.27; I2 = 0%). We performed subgroup analyses of the results of the study, the randomized controlled studies (OR = 0.31; 95% CI, 0.15–0.65; P < 0.001) as well as retrospective studies (OR = 0.28; 95% CI, 0.19–0.41; P < 0.001), 3–0 sutures (OR = 0.28; 95% CI, 0.17–0.45; P < 0.001) versus 4–0 sutures (OR = 0.26; 95% CI, 0.13–0.53; P < 0.001), barbed wire sutures (OR = 0.26; 95% CI, 0.14–0.48; P < 0.001) versus non-barbed wire sutures (OR = 0.30; 95% CI, 0.20–0.46; P < 0.001), interrupted (OR = 0.30, 95% CI, 0.20–0.46; P < 0.001) versus continuous sutures (OR = 0.29, 95% CI, 0.16–0.51; P < 0.001) to the anastomosis, full-thickness suture (OR = 0.29; 95% CI, 0.16–0.51; P < 0.001) versus sutured with the seromuscular layer (OR = 0.27; 95% CI, 0.14–0.53; P < 0.001), anastomotic sutured in one (OR = 0.27; 95% CI, 0.14–0.53; P < 0.001) versus non-one circle (OR = 0.30; 95% CI, 0.20–0.44; P < 0.001), and reinforcing sutures to the dog-ear area (OR = 0.26; 95% CI, 0.14–0.50; P < 0.001) versus the non–dog-ear area (OR = 0.30; 95% CI, 0.20–0.45; P < 0.001), which have suggested that there is no significant difference between each other and that all of them reduce the incidence of AL.ConclusionsThis study provides evidence that performing reinforcement suturing of the anastomosis during laparoscopic rectal surgery significantly lowers the incidence of postoperative AL but has no significant effect on anastomotic stenosis. It is important to note that further randomized controlled studies are required to confirm this conclusion.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022368631.

Background: Cardiovascular disease (CVD) is the leading cause of death worldwide, and statin therapy is the cornerstone of atherosclerotic cardiovascular disease. However, clinical practice is unsatisfactory, and there is significant interest in the risk of residual cardiovascular events. Traditional study methods make it difficult to exclude the crosstalk of confounding factors, and we investigated the impact of the ApoB/ApoA1 ratio on CVD using two-sample Mendelian randomization (MR) and multivariate Mendelian randomization (MVMR) methods. Methods: Two-sample MR and MVMR analyses were performed using pooled statistics from genome-wide association studies (GWAS) of ApoB/ApoA1 ratio (BAR), lipoprotein (a) (Lp(a)), and triglyceride (TG) in Europeans to assess the causal relationship between BAR, Lp(a), and TG with coronary artery disease (CAD). Results: The genetic prediction of BAR was significantly correlated with CAD (Inverse variance weighted (IVW) beta = 0.255; OR = 1.291; 95 % CI = 1.061–1.571; P = 0.011) in a two-sample MR analysis. MVMR studies showed that BAR (beta = 0.373; OR = 1.452; 95 % CI = 1.305–1.615; P = 7.217e-12), Lp (a) (beta = 0.238; OR = 1.269; 95 % CI = 1.216–1.323; P = 2.990e–28), and TG (beta = 0.155; OR = 1.168; 95 % CI = 1.074–1.270; P = 2.829e-04) were significantly associated with CAD. After further colinearity analyses of LASSO regressions, the results of multivariate analyses were similar for IVW, MR-Egger, MR-Lasso, and median methods. Conclusion: BAR is causally related to coronary artery disease. BAR is an independent predictor of CAD risk, independent of routine lipid measurements and other risk factors. TG and Lp(a) may be causally related to CAD, subject to verification in clinical practice.

Abstract Biochar application is widely recognized as an effective approach for increasing soil organic carbon (SOC) and mitigating climate change in agroecosystems. However, the effects of biochar application on net accumulations and relative contributions of different SOC sources remain unclear. Here, we explored the effects of biochar application on plant‐derived (PDC) and microbial necromass C (MNC) in a 10‐year experimental rice–wheat rotation field receiving four different intensities of biochar application (0, 2.25, 11.5, and 22.5 t ha−1 for each crop season), using phospholipid fatty acids (PLFAs), lignin phenols and amino sugars as biomarkers of microbial biomass, PDC and MNC, respectively. Our results showed that biochar application increased SOC content and stock by 32.6%–203% and 26.4%–145%, respectively. Higher biochar application (11.5 and 22.5 t ha−1) increased soil pH, total nitrogen (TN), total phosphorus (TP), SOC/TN, and root biomass. In addition, higher biochar application enhanced bacterial, fungal, and total microbial biomass. Plant lignin phenols and MNC contents significantly increased, whereas their contributions to SOC significantly decreased with the increase in biochar application rates due to the disproportionate increase in PDC and MNC, and SOC. Fungal necromass had a greater contribution to SOC than bacterial necromass. The fungal/bacterial necromass decreased from 2.56 to 2.26 with increasing biochar application rates, because of the higher abundances of bacteria than that of fungi as indicated by PLFAs under higher biochar application rates. Random forest analyses revealed that pH, TP, and SOC/TN were the main factors controlling plant lignin and MNC accumulation. Structural equation modeling revealed that biochar application increased lignin phenols by stimulating root biomass, whereas enhanced MNC accumulation was primarily from increased microbial biomass and lignin phenols. Overall, our findings suggest that biochar application increases the accumulation of the two SOC sources but decreases their contributions to SOC in paddy soils.

One of the fundamental objectives in ecology is to investigate the ecological processes and associated factors governing the abundance and spatial distribution patterns of biodiversity. However, the reaction of biological communities to environmental degradation remains relatively unknown, even for ecologically crucial communities like macroinvertebrates in aquatic ecosystems. Here, we sampled 117 locations to quantify relative contributions of geographical and environmental factors, including water quality, land use, climate, and hydrological factors, to determine the absolute and relative compositions of macroinvertebrate communities and their spatial distribution in the Yellow River Basin (YRB), the sixth-longest river system on Earth. We assessed relative roles of species sorting and dispersal in determining macroinvertebrate community structure along YRB. Our results demonstrated that alpha and beta diversity indices showed an increase from the up- to low-reaches of YRB. The middle and low-reaches exhibited elevated species diversity and both regions exhibited relatively stable community compositions. The biodiversity of macroinvertebrates was influenced by a combination of geographical factors and environmental variables, with environmental factors predominantly serving as the principal determinants. Results of multiple linear regression and variance decomposition showed that the effect of environmental factors was approximately three times greater than that of spatial factors. These findings provide support for the hypothesis that species sorting, driven by environmental gradients, plays a significant role in shaping the community structure of macroinvertebrates in running water ecosystems at the basin scales. Moreover, the factors contributing to substantial shifts in biodiversity across different segments of YRB indicate that distinct river sections have been influenced by varying stressors, with downstream areas being more susceptible to the impacts of water pollution and urbanization resulting from human activities.

Urban populations, especially women, are vunerable to exposure to airborne pollution, particularly inhalable particulates (PM10). Thus, more accurate measurement of PM10 levels and evaluating their health effects is critical for guiding policy to improve human health. Previous studies obtained personal PM10 with time-weighted average by air filter-based sampling (AFS), which ignores individual differences and behavioral patterns. Here, we used nasal filters instead of AFS to obtain actual inhaled PM10 under short-term exposure for urban dwelling women during a severe haze event in Beijing in 2016. The levels of six heavy metals such as As, Cd, Ni, Cr, Pb, and Co in PM10 were investigated, and carcinogenic and non-carcinogenic risks evaluated based on an adjusted US EPA health risk assessment model. The health endpoints for urban dwelling women were further assessed through an exposure-reponse model. We found that the hourly inhaled dose of PM10 obtained through the nasal filter was about 2.5–17.6 times that obtained by AFS, which also resulted in 4.41–11.30 times more morbidity than estimated by AFS (p 18.8 μg/kg·h) and heavy metals (>2.2 ng/kg·h), and these populations are therefore at greatest risk of developing non-cancer (HI = 4.16) and cancer (Rt = 7.8 × 10−3) related morbities.

In this work, the polysaccharide profile of different grapes and red wines in China was studied and the influences of two common winemaking techniques on the components of wine were analyzed. The soluble polysaccharide content in the skins of native grape species in China (non-Vitis vinifera grapes) was significantly higher than that of Vitis vinifera species, while the terroir effect on V. vinifera varieties was limited. The combination of the enzyme preparation and the addition of mannoproteins (MPs) at the beginning of alcoholic fermentation (MP1 + E) could increase the contents of MPs and acid polysaccharides (APS) compared to the control wines. Meanwhile, better color characteristics and higher level of anthocyanin derivatives were observed. However, MP1 + E treatment reduced the content of polysaccharides rich in arabinose and galactose (PRAGs) due to enzymatic hydrolysis. The study will provide useful information for winemakers to regulate the wine polysaccharide profile.

Magnetic reconnection is an important rapid energy release mechanism in astrophysics. Magnetic energy can be effectively converted into plasma kinetic energy, thermal energy, and radiation energy. This study is based on the magnetohydrodynamics simulation method and utilizes the FLASH code to investigate the laser-driven magnetic reconnection physical process of the Helmholtz capacitor-coil target. The simulation model incorporates the laser driving effect, and the external magnetic field consistent with the Helmholtz capacitor-coil target is written in. This approach achieves a magnetic reconnection process that is more consistent with the experiment. By changing the resistivity, subtle differences in energy conversion during the evolution of magnetic reconnection are observed. Under conditions of low resistivity, there is a more pronounced increase in the thermal energy of ions compared to other energy components. In simulations with high resistivity, the increase in electrons thermal energy is more prominent. The simulation gives the evolution trajectory of magnetic reconnection, which is in good agreement with the experimental results. This has important reference value for experimental research on the low-β magnetic reconnection.

IntroductionThe retina is a highly metabolically active tissue, and there is a lack of clarity about the relationship between metabolites and diabetic retinopathy (DR). This study used two-sample bidirectional Mendelian randomization (MR) analyses to identify causal relationships between metabolites and DR.MethodsGenetic variants were selected from the open-access Genome-Wide Association Studies (GWAS) summary database as proxies for the 1400 most recently published metabolites. MR analysis was performed to examine associations between these metabolite traits and DR. Single nucleotide polymorphism (SNP) data that were significantly associated with exposure were screened through association analysis. Validated instrumental variables (IVs) were obtained by removing SNPs with linkage disequilibrium (LD) and F-statistic values below 10. MR analyses were performed using the inverse variance weighted (IVW) method as the primary approach. The robustness of the results was verified by sensitivity analyses, including assessments of heterogeneity, horizontal pleiotropy, and the leave-one-out method.ResultsIn the IVW approach and in the primary analysis of several sensitivity analyses, genetically determined glycolithocholate sulfate levels, androstenediol (3 beta, 17 beta) monosulfate (1) levels, 1-stearoyl-2-arachidonoyl-GPE (18:0/20:4) levels, 1-oleoyl-2-arachidonoyl-GPE (18:1/20:4) levels, 1-oleoyl-2-linoleoyl-GPE (18:1/18:2) levels, X-26109 levels, N6-methyllysine levels, (N6,N6-dimethyllysine levels), and (N2-acetyl,N6,N6-dimethyllysine levels) were negatively associated with the risk of DR. 5-hydroxymethyl-2-furoylcarnitine levels and the glutamate-to-alanine ratio were positively associated with the risk of DR. No reverse causal association was found between DR and metabolites.DiscussionThis MR study suggests that nine metabolites may have a protective effect in DR, while two metabolites may be associated with an increased risk of DR. However, further research is needed to confirm these findings. Supplementation with beneficial metabolites may reduce DR risk and could potentially be a novel therapeutic approach to DR treatment.

Abstract Background Previous models for predicting delirium after cardiac surgery remained inadequate. This study aimed to develop and validate a machine learning-based prediction model for postoperative delirium (POD) in cardiac valve surgery patients. Methods The electronic medical information of the cardiac surgical intensive care unit (CSICU) was extracted from a tertiary and major referral hospital in southern China over 1 year, from June 2019 to June 2020. A total of 507 patients admitted to the CSICU after cardiac valve surgery were included in this study. Seven classical machine learning algorithms (Random Forest Classifier, Logistic Regression, Support Vector Machine Classifier, K-nearest Neighbors Classifier, Gaussian Naive Bayes, Gradient Boosting Decision Tree, and Perceptron.) were used to develop delirium prediction models under full (q = 31) and selected (q = 19) feature sets, respectively. Result The Random Forest classifier performs exceptionally well in both feature datasets, with an Area Under the Curve (AUC) of 0.92 for the full feature dataset and an AUC of 0.86 for the selected feature dataset. Additionally, it achieves a relatively lower Expected Calibration Error (ECE) and the highest Average Precision (AP), with an AP of 0.80 for the full feature dataset and an AP of 0.73 for the selected feature dataset. To further evaluate the best-performing Random Forest classifier, SHAP (Shapley Additive Explanations) was used, and the importance matrix plot, scatter plots, and summary plots were generated. Conclusions We established machine learning-based prediction models to predict POD in patients undergoing cardiac valve surgery. The random forest model has the best predictive performance in prediction and can help improve the prognosis of patients with POD.

Abstract Objective The objective of this study was to explore the associations of body mass index (BMI), fat mass index (FMI), skeletal mass index (SMI) and secondary osteoporosis (OP) in patients with rheumatoid arthritis (RA). Methods The bone mineral density (BMD) at sites of the femur neck (Neck), total hip (Hip) and lumbar vertebrae 1–4 (L1-4) was measured by dual-energy X-ray absorptiometry. The skeletal muscle index, body fat percentage and mineral content were measured by biological electrical impedance for calculating BMI, FMI and SMI. Results A total of 433 patient with RA and 158 healthy controls were enrolled. The BMDs at each site of the RA patients were lower compared with those of the healthy controls (p

Abstract Surgical procedures often rely on unaided visual observation or endoscopic assistance, which may pose challenges in cases involving intricate anatomical relationships. Real-time imaging technologies capable of intraoperative visualization of target organs have the potential to enhance the precision of surgical procedures by facilitating accurate identification, separation, and protection of vital tissues or organs. Despite these advantages, the widespread adoption of such technologies has been hindered by factors such as the prohibitive cost of equipment. This study aims to optimize and develop a device based on Indocyanine Green (ICG) for fluorescence imaging. The objective is to monitor changes in the average fluorescence intensity of ICG in the bladder, offering valuable guidance for surgeries involving the bladder. 1. Male rabbits were administered 0.01 mg/ml ICG via the renal pelvis and ear vein to obtain fluorescence images of the ureter, bladder, and small intestine. 2. After ligating the bilateral ureters of male rabbits, a retrograde bladder perfusion of 5 ml 0.01 mg/ml ICG was conducted to capture fluorescence images of the bladder over time. The average fluorescence intensity was computed using Image Pro Plus 6.0, and the corresponding curve was generated using Prism 8.0. Using a similar methodology, the average fluorescence intensity of male rabbits without ureteral ligation was measured and plotted over time. 1. The developed device facilitated imaging of the ureter, bladder, and small intestine. 2. The bladder's average fluorescence intensity exhibited changes over time in response to urine production and ureteral ligation, contrasting with observations without ureteral ligation. We have successfully constructed and optimized a modular fluorescence imaging system for organs and tissues. This system proves effective in imaging experiments involving hollow organs in animals and offers valuable insights for relevant surgical procedures.

Autoimmune hepatitis (AIH) is an inflammatory chronic liver disease with persistent and recurrent immune-mediated liver injury. The exact cause of AIH is still not fully understood, but it is believed to be primarily due to an abnormal activation of the immune system, leading to autoimmune injury caused by the breakdown of autoimmune tolerance. Although the pathogenesis of AIH remains unclear, recent studies have shown that abnormalities in amino acid metabolism play significant roles in its development. These abnormalities in amino acid metabolism can lead to remodeling of metabolic processes, activation of signaling pathways, and immune responses, which may present new opportunities for clinical intervention in AIH. In this paper, we first briefly outline the recent progress of clinically relevant research on AIH, focusing on the role of specific amino acid metabolism (including glutamine, cysteine, tryptophan, branched-chain amino acids, etc.) and their associated metabolites, as well as related pathways, in the development of AIH. Furthermore, we discuss the scientific issues that remain to be resolved regarding amino acid metabolism, AIH development and related clinical interventions, with the aim of contributing to the future development of amino acid metabolism-based as a new target for the clinical diagnosis and treatment of AIH.

ObjectivesTo analyze the clinical and imaging characteristics of autoimmune glial fibrillary acidic protein astrocytopathy (GFAP-A).MethodsForty-three patients diagnosed with GFAP-A between March 2017 and July 2023 were retrospectively recruited. The clinical characteristics and magnetic resonance imaging (MRI) features were collected.ResultsTwenty-one patients (61.8%) had a fever and 16 (47.1%) had a headache. Five patients (14.7%) had coexisting neural autoantibodies and one patient (2.9%) had a coexisting neoplasm. The most common presentation was meningoencephalomyelitis (13/34, 38.3%), followed by meningoencephalitis (12/34, 35.3%). The other clinical manifestations included blurred visions (5/34, 14.7%) and peripheral nervous system involvement (4/34, 11.8%). Twenty-six patients (76.5%) had elevated nucleated cell count, predominantly lymphocytes (15/15, 100%), and 27 (79.4%) had elevated protein levels of cerebrospinal fluid. One-half (50%) of the patients presented with hyponatremia. A majority of the patients (30/33, 90.9%) exhibited abnormal hyperintense lesions on T2WI, which were often located in juxtacortical white matter (18/33, 54.5%), followed by periventricular white matter (16/33, 48.5%), basal ganglia (15/ 33, 45.5%), brainstem (11/33, 33.3%), and thalamic lesions (9/33, 27.3%). Twenty-four patients (72.7%) had abnormal brain enhancement, with supratentorial leptomeningeal enhancement being the most frequent enhancement pattern (15/33, 45.5%), followed by linear perivascular radial enhancement (14/33, 42.4%). Nineteen patients (70.4%) had hyperintense intramedullary spinal cord lesions, with long segments (15/27, 55.6%) and transverse lesions (14/27, 51.9%) being the most frequent lesions. Most cases were sensitive to immunotherapy, such as glucocorticoids, intravenous immunoglobulin, and tacrolimus, with three patients (8.8%) experiencing relapses. Patients with brainstem lesions had higher onset modified Rankin scale scores and were more prone to intensive care unit admissions. Linear perivascular radial enhancement was positively associated with poor prognosis (p

A novel three-dimensional asymmetric oscillating heat pipe (3DAOHP) with unequal curvature radius of upper and lower bends has been designed. Setting the basic factor of diameter from 1.9 mm to 6.2 mm, a verification experiment on the criterion of conventional maximum hydraulic diameter (MHD) has been conducted. The results show that the 3DAOHP can still perform normally and transfer heat effectively, even if the diameter exceeds the MHD by 98.1 %. And the temperature profiles at each end does not show obvious abnormalities. The thermal performance also does not show any deterioration, which still follows the rule that the larger the diameter, the stronger the heat transfer capability. The thermal resistance of the 6.2 mm 3DAOHP can reach 0.07 °C/W at 1300 W without touching the dry-out limit. Moreover, the frequency and amplitude of hot end temperature fluctuation show suppression as the diameter increases. Therefore, the conventional MHD is not a diameter limitation of oscillating heat pipe (OHP) in enhancing heat transfer. Thus, the availability of OHP in high heat loads can be improved by further increasing the tube diameter. These findings are important for the OHP application in higher heat flux.

Natural product biosynthesis is controlled at multiple levels. Characterization of naturally occurring promoters has facilitated the study of the synthetic biology of natural products. Herein, we report the discovery of two high-yield actinomycin D (ActD)-producing streptomycetes and the identification of a strong bidirectional acmN2p promoter from the ActD gene clusters and its application in heterologous expression of three core genes involved in the bacterial alkaloid bohemamine biosynthesis, providing a good example for identification of new promoters for synthetic biological applications.

In pipe jacking engineering, accurate prediction of jacking force is the key to pipe jacking design. Based on a project of the Beijing Daxing Airport Line, the influence of the advance jacked pipes on the jacking force of the subsequent pipe is carried out in the present work. First, the verified numerical model of practical engineering was established, and the jacking force and radial stress of different pipes were analyzed. Then, the two pipes were taken as research object, and the parameters of spacing, angle, buried depth, and pipe diameter were investigated, respectively. The results show that in the actual project, the advance jacked pipes have amplification and superposition effects on friction resistance of the subsequent pipe, and the maximum growth rate is 37.2%. The friction resistance of the subsequent pipe presents a trend of first increasing and then decreasing with the change of the layout angle of advance jacked pipe from 0° to 180°. With the increase of buried depth and pipe diameter, the absolute value of incremental friction resistance of the subsequent pipe increases gradually, but the growth rate remains constant. Finally, the empirical formulas for predicting the friction resistance growth rate of subsequent pipes under different angles are proposed. The research results can provide some reference for the design of pipe jacking.

Abstract Despite being a new promising tool for cancer therapy, intravenous delivery of oncolytic viruses (OVs) is greatly limited by poor tumor targeting, rapid clearance in the blood, severe organ toxicity, and cytokine release syndrome. Herein, a simple and efficient strategy of erythrocyte‐leveraged oncolytic virotherapy (ELeOVt) is reported, which for the first time assembled OVs on the surface of erythrocytes with up to near 100% efficiency and allowed targeted delivery of OVs to the lung after intravenous injection to achieve excellent treatment of pulmonary metastases while greatly improving the biocompatibility of OVs as a drug. Polyethyleneimine (PEI) as a bridge to assemble OVs on erythrocytes also played an important role in promoting the transfection of OVs. It is found that ELeOVt approach significantly prolonged the circulation time of OVs and increased the OVs distribution in the lung by more than tenfold, thereby significantly improving the treatment of lung metastases while reducing organ and systemic toxicity. Taken together, these findings suggest that the ELeOVt provides a biocompatible, efficient, and widely available approach to empower OVs to combat lung metastasis.

Summary: ISG15 is a type I interferon-induced ubiquitin-like modifier that functions in innate immune responses. The major human ISG15 ligase is hHERC5, a ribosome-associated HECT E3 that broadly ISGylates proteins cotranslationally. Here, we characterized the hHERC5-dependent ISGylome and identified over 2,000 modified lysines in over 1,100 proteins in IFN-β-stimulated cells. In parallel, we compared the substrate selectivity hHERC5 to the major mouse ISG15 ligase, mHERC6, and analysis of sequences surrounding ISGylation sites revealed that hHERC5 and mHERC6 have distinct preferences for amino acid sequence context. Several features of the datasets were consistent with ISGylation of ribosome-tethered nascent chains, and mHERC6, like hHERC5, cotranslationally modified nascent polypeptides. The ISGylome datasets presented here represent the largest numbers of protein targets and modification sites attributable to a single Ub/Ubl ligase and the lysine selectivities of the hHERC5 and mHERC6 enzymes may have implications for the activities of HECT domain ligases, generally.

Seaweed farming has made outstanding contributions to food supply and the restoration of the ecological environment despite the limitations in production and ecological effects due to the current intensive farming of single algae species. These limitations can be overcome by selecting suitable algal species based on their physiological characteristics and by constructing a large-scale seaweed rotation model. This study carried out a trial culture in aquaculture sea areas, and performed in situ monitoring of the environmental conditions and physiological characteristics of Saccharina japonica, Hizikia fusiformis, and Gracilariopsis lemaneiformis. Additionally, a comparative analysis of the three macroalgae at different times was conducted to determine their response characteristics to environmental factors. The results showed that: (1) The three macroalgae had varying light tolerance. The effective quantum yield of Hizikia fusiformis and Gracilariopsis lemaneiformis remained unchanged during the changes in light environment, while that of Saccharina japonica first decreased and then recovered. (2) The relative electron transport rates of the three macroalgae were significantly different under different temperature conditions. Hizikia fusiformis and Saccharina japonica exhibited the highest relative electron transport rates (70.45 and 106.75, respectively) in May (20.3 °C). Notably, Gracilariopsis lemaneiformis demonstrated good growth and exhibited the highest relative electron transport rate (93.07) in September (27.5 °C). These findings collectively support the feasibility of establishing a macroalgae rotation model. Based on the combined environmental conditions of the seas in Shandong, Zhejiang, and Fujian, a macroalgae rotation model was proposed. The application of this model in the construction of artificial seaweed farms in marine ranches can provide a stable output of large-scale seaweed production and ecological benefits.

The rocket sled, as a ground dynamic test system, combines the characteristics of the wind tunnel test and the flight test. However, some practical factors, such as shock wave interference, ground effect, and high-intensity aerodynamic noise will cause serious interference and even failure of the uniformly distributed sensors during horizontal sliding in a wide speed range. The AGARD HB-2 standard model is employed as the payload to simulate the aerodynamic and aeroacoustic characteristics during the variable acceleration period, aiming to optimize the test sensors layout. It is observed that in the high Mach number flow fields, strong coupling behaviors among complex waves will occur. The peak of wake vortex strength will appear at 1.5 s and gradually diminish over time. In addition, when the vortex between the load and the booster is monitored, its position shifts forward in the subsonic stage, then gradually moves backward and expands in the supersonic stage. Acoustic directivity is pronounced at subsonic and transonic speeds, pointing towards 75° and 135° relative to the sliding speed, respectively. These results can provide technical support for sensor layout and high-precision testing in rocket sled tests.

Vector polygons represent crucial survey data, serving as a cornerstone of national geographic censuses and forming essential data sources for detecting geographical changes. The timely update of these polygons is vital for governmental decision making and various industrial applications. However, the manual intervention required to update existing vector polygons using up-to-date high-resolution remote sensing (RS) images poses significant challenges and incurs substantial costs. To address this, we propose a novel change detection (CD) method for land cover vector polygons leveraging high-resolution RS images and deep learning techniques. Our approach begins by employing the boundary-preserved masking Simple Linear Iterative Clustering (SLIC) algorithm to segment RS images. Subsequently, an adaptive cropping approach automatically generates an initial sample set, followed by denoising using the efficient Visual Transformer and Class-Constrained Density Peak-Based (EViTCC-DP) method, resulting in a refined training set. Finally, an enhanced attention-based multi-scale ConvTransformer network (AMCT-Net) conducts fine-grained scene classification, integrating change rules and post-processing methods to identify changed vector polygons. Notably, our method stands out by employing an unsupervised approach to denoise the sample set, effectively transforming noisy samples into representative ones without requiring manual labeling, thus ensuring high automation. Experimental results on real datasets demonstrate significant improvements in model accuracy, with accuracy and recall rates reaching 92.08% and 91.34%, respectively, for the Nantong dataset, and 93.51% and 92.92%, respectively, for the Guantan dataset. Moreover, our approach shows great potential in updating existing vector data while effectively mitigating the high costs associated with acquiring training samples.

Epidemics are dangerous and difficult to prevent and control, especially in urban areas. Clarifying the correlation between the COVID-19 Outbreak Frequency and the urban spatial environment may help improve cities’ ability to respond to such public health emergencies. In this study, we firstly analyzed the spatial distribution characteristics of COVID-19 Outbreak Frequency by correlating the geographic locations of COVID-19 epidemic-affected neighborhoods in the city of Beijing with the time point of onset. Secondly, we created a geographically weighted regression model combining the COVID-19 Outbreak Frequency with the external spatial environmental elements of the city. Thirdly, different grades of epidemic-affected neighborhoods in the study area were classified according to the clustering analysis results. Finally, the correlation between the COVID-19 Outbreak Frequency and the internal spatial environmental elements of different grades of neighborhoods was investigated using a binomial logistic regression model. The study yielded the following results. (i) Epidemic outbreak frequency was evidently correlated with the urban external spatial environment, among building density, volume ratio, density of commercial facilities, density of service facilities, and density of transportation facilities were positively correlated with COVID-19 Outbreak Frequency, while water and greenery coverage was negatively correlated with it. (ii) The correlation between COVID-19 Outbreak Frequency and the internal spatial environmental elements of neighborhoods of different grades differed. House price and the number of households were positively correlated with the COVID-19 Outbreak Frequency in low-end neighborhoods, while the number of households was positively correlated with the COVID-19 Outbreak Frequency in mid-end neighborhoods. In order to achieve spatial justice, society should strive to address the inequality phenomena of income gaps and residential differentiation, and promote fair distribution of spatial environments.

After the rupture of pressurized water supply pipes in urban underground areas, seepage-induced ground subsidence becomes a severe geological hazard. Understanding the permeation and diffusion patterns of water in soil is crucial for deciphering the mechanisms underlying soil settlement and damage. Notably, the pressure within water supply pipes significantly influences the settlement and damage of the soil. Therefore, this study simulated experiments on soil settlement and damage caused by water seepage from a preexisting damaged pipeline under various internal pipe pressure conditions using an indoor model apparatus. The results indicate that the internal pressure of the pipe significantly influences the settlement of the soil. High-pressure seepage causes noticeable erosion in the soil, forming cavities within it. In contrast, low-pressure seepage results in water diffusing in an ellipsoidal pattern, leading to the formation of circular surface cracks. The degree of surface settlement increases with higher pipe pressure. The onset of subsidence at a specific point on the ground is not directly related to whether the moistening front within the soil has reached that point horizontally. Instead, it is associated with the moisture content below the subsidence point within the soil. The research results further illustrate the water diffusion and moisture content increase processes after water seepage from pipes with different pressures, revealing the influence of pipe pressure on the degree and form of soil settlement damage and clarifying the relationship between water diffusion and settlement in the soil.

The main severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) protease (Mpro, also known as 3CLpro) plays a central role in virus replication, thereby constituting an appealing therapeutic target for coronavirus disease 2019 (COVID-19) treatment. In this study, we used recently reported crystal structures of SARS-CoV-2 Mpro complexed with small-molecule inhibitors. Using the established structure–activity relationships of small-molecule inhibitors of the Mpro of SARS-CoV-2, we used the Virtual Screening Workflow (with hydrogen bond constraints) implemented in Schrödinger Suite 2021 to screen approximately one million compounds in the ChemDiv compound library to identify potential novel noncovalent Mpro inhibitors. Our docking analysis yielded 65 promising lead compounds, the inhibitory activity of which against Mpro was assessed using a fluorescent SARS-CoV-2 Mpro inhibition assay. Notably, six compounds exhibited SARS-CoV-2 Mpro inhibition with IC50 values ranging 22.95–64.63 μM. These hit compounds exhibited good structural diversity, which prompted us to investigate their SARS-CoV-2 Mpro binding modes. We used a previously validated IFD-BPMD-MD workflow to predict the binding positions of these hit compounds. Our simulations showed that these hit complexes exhibited diverse and robust binding to the SARS-CoV-2 Mpro. Our study findings offer valuable insights into the development of novel noncovalent small-molecule protease inhibitor.

Abstract Aim The objective of this study is to comprehensively evaluate the therapeutic efficacy of postmastectomy radiotherapy (PMRT) in treating patients with pT3N0‐1M0 breast cancer within the context of modern therapeutic strategies. Methods Clinical data from patients with pT3N0‐1M0 breast cancer who underwent mastectomy from January 2005 to December 2018 at our institution were retrospectively analyzed. Results The study involved a total of 222 participants, with 112 individuals undergoing PMRT and 110 individuals not receiving it. The median follow‐up duration was 77 months (range: 6–171 months). The entire cohort demonstrated 5‐year disease‐free survival (DFS) and overall survival (OS) rates of 85.1% and 91.0%, respectively, along with a locoregional recurrence (LRR) rate as low as 7.2%. The PMRT group showed significantly better 5‐year DFS (90.2% vs. 80.0%, p = 0.02) and OS (95.5% vs. 86.4%, p = 0.012) rates, as well as a lower LRR rate (4.5% vs. 10.0%, p = 0.122), compared to the group without PMRT. Cox regression analysis confirmed the independent prognostic significance of PMRT for both DFS (p = 0.040) and OS (p = 0.047). Following propensity score matching (PSM), the analysis included 100 matched patients, revealing an improved prognosis for those who received PMRT (DFS: p = 0.067; OS: p = 0.043). Conclusions Our study reveals favorable prognoses for pT3N0‐1M0 breast cancer patients treated within contemporary therapeutic approaches. The pivotal role of PMRT in this context is evident. However, due to the retrospective design of our study and the relatively limited sample size, further investigation is imperative to validate and enhance these initial findings.

Aims. To evaluate the impact of neutrophil-to-lymphocyte ratio (NLR) on periprocedural pulmonary hypertension (PH) and 3-month all-cause mortality in patients with aortic stenosis (AS) who underwent transcatheter aortic valve replacement (TAVR) and to develop a nomogram for predicting the mortality for these patients. Methods and Results. 124 patients undergoing TAVR were categorized into three groups according to systolic pulmonary artery pressure (sPAP): Group I (no PH, n = 61) consisted of patients with no pre- and post-TAVR PH; Group II (improved PH, n = 35) consisted of patients with post-TAVR systolic pulmonary artery pressure (sPAP) decreased by more than 10 mmHg compared to pre-TAVR levels; and Group III (persistent PH, n = 28) consisted of patients with post-TAVR sPAP no decrease or less than 10 mmHg, or new-onset PH after the TAVR procedure. The risk of all-cause mortality within 3 months tended to be higher in Group II (11.4%) and Group III (14.3%) compared to Group I (3.3%) (P=0.057). The multinomial logistic regression analysis demonstrated a positive correlation between NLR and both improved PH (OR: 1.182, 95% CI: 1.036–1.350, P=0.013) and persistent PH (OR: 1.181, 95% CI: 1.032–1.352, P=0.016). Kaplan–Meier analysis revealed a significant association between higher NLR and increased 3-month all-cause mortality (16.1% vs. 3.1% in lower NLR group, P=0.021). The multivariable Cox regression analysis confirmed that NLR was an independent predictor for all-cause mortality within 3 months, even after adjusting for clinical confounders. A nomogram incorporating five factors (BNP, heart rate, serum total bilirubin, NLR, and comorbidity with coronary heart disease) was developed. ROC analysis was performed to discriminate the ability of the nomogram, and the AUC was 0.926 (95% CI: 0.850–1.000, P

In this investigation, the mechanism of dye transfer during the mixed washing of natural cellulosic fabrics was elucidated through a comprehensive study of the hydrolysis of Reactive Red 195 (RR 195) and the subsequent adsorption of its hydrolysis products onto cellulose, approached both experimentally and theoretically. Initially, Reversed-phase high-performance liquid chromatography (RP-HPLC) was employed to identify the final products of Reactive Red 195 hydrolysis, collectively referred to as the unfixed dye substance ( UDS ). This data provided theoretical insight into the hydrolysis mechanism of the dye. Following this identification, an adsorption kinetic model was established to delineate the interaction of the hydrolysis products with cellulose. Adsorption exhibited its maximal rate at a temperature of 60°C, under conditions of a wash bath ratio of 120:1 and a pH value of 7. Furthering the investigation, a molecular dynamics model was constructed to detail the adsorption process of these hydrolysis products on the hydrophobic surface Iβ(1 0 0) of cellulose within an aqueous environment. This model offered precise insights into the adsorption volume, kinetics, and mechanistic interaction at a molecular scale. Conclusive evidence from both theoretical analyses and experimental results suggested that the hydrolysis products, devoid of reactive groups, were incapable of chemically interacting with the hydroxyl groups inherent to cellulose. Instead, it was discerned that these products underwent a physical adsorption process onto the cellulose surface. Such adsorptive behavior is postulated to be a predominant factor influencing the dye transfer phenomenon in mixed washing conditions.

Through whole-genome re-sequencing of 18 Hymenopellis radicata germplasm resources collected from diverse regions in China, we identified significant variations in the form of Single Nucleotide Polymorphisms (SNPs) and Insertions and Deletions (InDels). These variations were comprehensively annotated, shedding light on the mutation types present in the entire genome of the H. radicata germplasm. This analysis revealed the number and position information of each mutation and provided insights into the overall genomic landscape of H. radicata germplasm. Utilizing SNP data, we delved into the population structure of the 18 H. radicata germplasm resources. The results indicated the presence of 2,335,179 Indel sites and 12,050,448 SNP sites. The population structure analysis unveiled two distinct subgroups among the H. radicata germplasm resources. Phenotypic statistics, principal component analysis, and phylogenetic tree results echoed the findings of the population structure analysis. Different strains of H. radicata from various regions in China exhibited notable differences in genetic diversity, mycelial growth rate, yield, and fruiting body characteristics. Significant disparities were observed between the two subgroups, while strains within each subgroup shared common characteristics. This research establishes a solid foundation for integrating H. radicata into diverse breeding programs. The data underscore the potential of H. radicata for genetic improvement and exploitation in breeding initiatives, paving the way for future advancements in this field.

With the continuous promotion of the unified electricity spot market in the southern region, the formation mechanism of spot market price and its forecast will become one of the core elements for the healthy development of the market. Effective spot market price prediction, on one hand, can respond to the spot power market supply and demand relationship; on the other hand, market players can develop reasonable trading strategies based on the results of the power market price prediction. The methods adopted in this paper include: Analyzing the principle and mechanism of spot market price formation. Identifying relevant factors for electricity price prediction in the spot market. Utilizing a clustering model and Spearman’s correlation to classify diverse information on electricity prices and extracting data that aligns with the demand for electricity price prediction. Leveraging complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN) to disassemble the electricity price curve, forming a multilevel electricity price sequence. Using an XGT model to match information across different levels of the electricity price sequence. Employing the ocean trapping algorithm-optimized Bidirectional Long Short-Term Memory (MPA-CNN-BiLSTM) to forecast spot market electricity prices. Through a comparative analysis of different models, this study validates the effectiveness of the proposed MPA-CNN-BiLSTM model. The model provides valuable insights for market players, aiding in the formulation of reasonable strategies based on the market's supply and demand dynamics. The findings underscore the importance of accurate spot market price prediction in navigating the complexities of the electricity market. This research contributes to the discourse on intelligent forecasting models in electricity markets, supporting the sustainable development of the unified spot market in the southern region.

In recent years, with the increasing global focus on environmental protection, the issue of microfiber release from denim during the washing process has gained attention. In this study, a programmable washing device simulating household drum washing was designed and developed, microfibers and indigo dyes released from denim washing were quantitatively detected, and we have also developed a novel method for estimating the release of microfibers during washing. The effects of washing time, washing temperature, and washing load on microfiber and indigo dye release from denim were explored. The results showed that the effect of washing load on microfiber and indigo dye release was greater than washing temperature and washing time. The research findings indicate that with an increase in washing time (35–95 min) and washing load (100–250 g), the shedding of microfibers and indigo dye significantly increases, reaching peak release levels of 343.6 μg/g fabric and 0.027 mg/L, respectively. However, there is a decreasing trend in the release of microfibers and indigo dye when the washing temperature exceeds 50 °C. Furthermore, our data suggests that an increase in washing load leads to a significant change in the number of microfibers (from 978 items/g fabric to 1997 items/g fabric) and their mass (from 156.87 μg/g fabric to 343.56 μg/g fabric). The influence of washing time, washing temperature, and washing load on microfiber length shows relatively small fluctuations within the range of 600–900 µm. This study provides new ideas and methods for estimating the release of microfiber and indigo dye in denim washing around the world.